def Initialize(self, indim, outdim):
self.warp = 1000.0 # let the samples flowing into the ring buffer set the pace
self.eegfs = self.samplingrate()
self.hwfs = int(self.params['HardwareSamplingRate'])
self.chunk = SigTools.msec2samples(
float(self.params['HardwareChunkMsec']), self.hwfs)
ringsize = SigTools.msec2samples(
float(self.params['NIABufferSizeMsec']), self.hwfs)
self.ring = SigTools.ring(ringsize, indim[0])
self.ring.allow_overflow = True
self.nominal['HardwareSamplesPerPacket'] = SigTools.msec2samples(
self.nominal['SecondsPerPacket'] * 1000.0, self.hwfs)
cutoff = float(self.params['DSFilterFreqFactor']) * self.eegfs / 2.0
order = int(self.params['DSFilterOrder'])
if order > 0 and cutoff > 0.0:
self.filter = SigTools.causalfilter(
freq_hz=cutoff,
samplingfreq_hz=self.hwfs,
order=order,
type='lowpass') #, method=SigTools.firdesign)
else:
self.filter = None
self.dsind = numpy.linspace(0.0,
self.nominal['HardwareSamplesPerPacket'],
self.nominal['SamplesPerPacket'] + 1,
endpoint=True)
self.dsind = numpy.round(self.dsind).astype(numpy.int).tolist()
self._threads['listen'].post('start')
self._threads['listen'].read('ready', wait=True, remove=True)
self._check_threads()
def initialize(cls, app, indim, outdim):
if int(app.params['ERPDatabaseEnable'])==1:
if int(app.params['ShowSignalTime']):
app.addstatemonitor('LastERPVal')
app.addstatemonitor('ERPCollected')
#===================================================================
# Prepare the buffers for saving the data
# -leaky_trap contains the data to be saved (trap size defined by pre_stim_samples + post_stim_samples + some breathing room
# -trig_trap contains only the trigger channel
#===================================================================
app.x_vec=np.arange(app.erpwin[0],app.erpwin[1],1000.0/app.eegfs,dtype=float)#Needed when saving trials
app.post_stim_samples = SigTools.msec2samples(app.erpwin[1], app.eegfs)
app.pre_stim_samples = SigTools.msec2samples(np.abs(app.erpwin[0]), app.eegfs)
app.leaky_trap=SigTools.Buffering.trap(app.pre_stim_samples + app.post_stim_samples + 5*app.spb, len(app.params['ERPChan']), leaky=True)
app.trig_trap = SigTools.Buffering.trap(app.post_stim_samples, 1, trigger_channel=0, trigger_threshold=app.trigthresh[0])
#===================================================================
# Prepare the models from the database.
#===================================================================
app.subject = Subject.objects.get_or_create(name=app.params['SubjectName'])[0]
#===================================================================
# app.period = app.subject.get_or_create_recent_period(delay=0)
# app.subject.periods.update()
# app.period = app.subject.periods.order_by('-datum_id').all()[0]
#===================================================================
#===================================================================
# Use a thread for database interactions because sometimes they will be slow.
# (especially when calculating a trial's features)
#===================================================================
app.erp_thread = ERPThread(Queue.Queue(), app)
app.erp_thread.setDaemon(True) #Dunno, always there in the thread examples.
app.erp_thread.start() #Starts the thread.
#===================================================================
# Setup the ERP feedback elements.
# -Screen will range from -2*fbthresh to +2*fbthresh
# -Calculated ERP value will be scaled so 65536(int16) fills the screen.
#===================================================================
if int(app.params['ERPFeedbackDisplay'])==2:
fbthresh = app.params['ERPFeedbackThreshold'].val
app.erp_scale = (2.0**16) / (4.0*np.abs(fbthresh))
if fbthresh < 0:
fbmax = fbthresh * app.erp_scale
fbmin = 2.0 * fbthresh * app.erp_scale
else:
fbmax = 2.0 * fbthresh * app.erp_scale
fbmin = fbthresh * app.erp_scale
m=app.scrh/float(2**16)#Conversion factor from signal amplitude to pixels.
b_offset=app.scrh/2.0 #Input 0.0 should be at this pixel value.
app.addbar(color=(1,0,0), pos=(0.9*app.scrw,b_offset), thickness=0.1*app.scrw, fac=m)
n_bars = len(app.bars)
#app.stimuli['bartext_1'].position=(50,50)
app.stimuli['bartext_' + str(n_bars)].color=[0,0,0]
erp_target_box = Block(position=(0.8*app.scrw,m*fbmin+b_offset), size=(0.2*app.scrw,m*(fbmax-fbmin)), color=(1,0,0,0.5), anchor='lowerleft')
app.stimulus('erp_target_box', z=1, stim=erp_target_box)
def Initialize(self, indim, outdim):
self.warp = 1000.0 # let the samples flowing into the ring buffer set the pace
self.eegfs = self.samplingrate()
self.hwfs = int(self.params['HardwareSamplingRate'])
self.chunk = SigTools.msec2samples(float(self.params['HardwareChunkMsec']), self.hwfs)
ringsize = SigTools.msec2samples(float(self.params['NIABufferSizeMsec']), self.hwfs)
self.ring = SigTools.ring(ringsize, indim[0])
self.ring.allow_overflow = True
self.nominal['HardwareSamplesPerPacket'] = SigTools.msec2samples(self.nominal['SecondsPerPacket']*1000.0, self.hwfs)
cutoff = float(self.params['DSFilterFreqFactor']) * self.eegfs / 2.0
order = int(self.params['DSFilterOrder'])
if order > 0 and cutoff > 0.0:
self.filter = SigTools.causalfilter(freq_hz=cutoff, samplingfreq_hz=self.hwfs, order=order, type='lowpass') #, method=SigTools.firdesign)
else:
self.filter = None
self.dsind = numpy.linspace(0.0, self.nominal['HardwareSamplesPerPacket'], self.nominal['SamplesPerPacket']+1, endpoint=True)
self.dsind = numpy.round(self.dsind).astype(numpy.int).tolist()
self._threads['listen'].post('start')
self._threads['listen'].read('ready', wait=True, remove=True)
self._check_threads()
def initialize(cls, app, indim, outdim):
if int(app.params['ERPDatabaseEnable']) == 1:
if int(app.params['ShowSignalTime']):
app.addstatemonitor('LastERPVal')
app.addstatemonitor('ERPCollected')
#===================================================================
# Prepare the buffers for saving the data
# -leaky_trap contains the data to be saved (trap size defined by pre_stim_samples + post_stim_samples + some breathing room
# -trig_trap contains only the trigger channel
#===================================================================
app.x_vec = np.arange(app.erpwin[0],
app.erpwin[1],
1000.0 / app.eegfs,
dtype=float) #Needed when saving trials
app.post_stim_samples = SigTools.msec2samples(
app.erpwin[1], app.eegfs)
app.pre_stim_samples = SigTools.msec2samples(
np.abs(app.erpwin[0]), app.eegfs)
app.leaky_trap = SigTools.Buffering.trap(
app.pre_stim_samples + app.post_stim_samples + 5 * app.spb,
len(app.params['ERPChan']),
leaky=True)
app.trig_trap = SigTools.Buffering.trap(
app.post_stim_samples,
1,
trigger_channel=0,
trigger_threshold=app.trigthresh[0])
#===================================================================
# Prepare the models from the database.
#===================================================================
app.subject = Subject.objects.get_or_create(
name=app.params['SubjectName'])[0]
#===================================================================
# app.period = app.subject.get_or_create_recent_period(delay=0)
# app.subject.periods.update()
# app.period = app.subject.periods.order_by('-datum_id').all()[0]
#===================================================================
#===================================================================
# Use a thread for database interactions because sometimes they will be slow.
# (especially when calculating a trial's features)
#===================================================================
app.erp_thread = ERPThread(Queue.Queue(), app)
app.erp_thread.setDaemon(
True) #Dunno, always there in the thread examples.
app.erp_thread.start() #Starts the thread.
#===================================================================
# Setup the ERP feedback elements.
# -Screen will range from -2*fbthresh to +2*fbthresh
# -Calculated ERP value will be scaled so 65536(int16) fills the screen.
#===================================================================
if int(app.params['ERPFeedbackDisplay']) == 2:
fbthresh = app.params['ERPFeedbackThreshold'].val
app.erp_scale = (2.0**16) / (4.0 * np.abs(fbthresh))
if fbthresh < 0:
fbmax = fbthresh * app.erp_scale
fbmin = 2.0 * fbthresh * app.erp_scale
else:
fbmax = 2.0 * fbthresh * app.erp_scale
fbmin = fbthresh * app.erp_scale
m = app.scrh / float(
2**16) #Conversion factor from signal amplitude to pixels.
b_offset = app.scrh / 2.0 #Input 0.0 should be at this pixel value.
app.addbar(color=(1, 0, 0),
pos=(0.9 * app.scrw, b_offset),
thickness=0.1 * app.scrw,
fac=m)
n_bars = len(app.bars)
#app.stimuli['bartext_1'].position=(50,50)
app.stimuli['bartext_' + str(n_bars)].color = [0, 0, 0]
erp_target_box = Block(position=(0.8 * app.scrw,
m * fbmin + b_offset),
size=(0.2 * app.scrw,
m * (fbmax - fbmin)),
color=(1, 0, 0, 0.5),
anchor='lowerleft')
app.stimulus('erp_target_box', z=1, stim=erp_target_box)
